This letter investigates the robust beamforming design for an integrated sensing and covert communications system, where the transmitter (Alice) performs some sensing task and simultaneously communicates with multiple legitimate users (Bobs) covertly, evading detection by the eavesdropper (Willie). Considering the impact of imperfect channel state information (CSI) of Alice-to-Bobs and Alice-to-Willie links, we formulate a robust beamforming optimization problem to minimize the Cramér-Rao bound for sensing parameter while satisfying the total transmit power, the signal-to-interference-plus-noise ratio and covertness constraints for communication. An iterative algorithm, employing semi-definite programming and successive convex approximation, is proposed to address this challenging problem. Numerical results validate the effectiveness of the proposed scheme, highlighting the robustness of the optimized beamforming design under imperfect CSI.
This letter investigates the robust beamforming design for an integrated sensing and covert communications system, where the transmitter (Alice) performs some sensing task and simultaneously communicates with multiple legitimate users (Bobs) covertly, evading detection by the eavesdropper (Willie). Considering the impact of imperfect channel state information (CSI) of Alice-to-Bobs and Alice-to-Willie links, we formulate a robust beamforming optimization problem to minimize the Cramér-Rao bound for sensing parameter while satisfying the total transmit power, the signal-to-interference-plus-noise ratio and covertness constraints for communication. An iterative algorithm, employing semi-definite programming and successive convex approximation, is proposed to address this challenging problem. Numerical results validate the effectiveness of the proposed scheme, highlighting the robustness of the optimized beamforming design under imperfect CSI.
Emerging wireless applications pursue a paradigm shift towards the integrated system that is capable of secure data transmission and high-resolution sensing in near-field environments. Conventional far-field use-cases suffer from the fundamental limitations in security, spatial precision, and spectral coexistence. Against this backdrop, this paper investigates an integrated covert communications and sensing (ICCS) system operating in the near-field environment. Specifically, the transmitter (Alice) aims to covertly convey messages to legitimate receivers (Bobs), while circumventing the detection by the eavesdropper (Willie) as well as improving the sensing performance at the target. To elevate communication performance, we aim to maximize the achievable sum rate to jointly optimize the communication and sensing beamforming matrices at Alice. The optimization problem is subject to multiple constraints with coupled variables: the transmit power budget at Alice, the minimum communication rate requirements for Bob, the Crameˊr-Rao bound (CRB) constraint to ensure accurate parameter estimation in sensing, and the covertness constraint against Willie’s detection. Given the non-convex nature of the formulated problem, an efficient successive convex approximation and semidefinite relaxation algorithms are proposed. In addition, we provide a theoretical analysis to confirm the convergence behaviour of the proposed algorithm, which can achieve the near-optimal solution. Finally, the numerical results are presented to highlight the superiority of the proposed ICCS system over existing counterparts. These results numerically verify the effectiveness of the proposed approach in enhancing communication rates while maintaining sensing performance and covertness in the near-field regime.
In this paper, we consider a common unicast beamforming network where Alice utilizes the communication to Carol as a cover and covertly transmits a message to Bob without being recognized by Willie. We investigate the beamformer design of Alice to maximize the covert rate to Bob when Alice has either perfect or imperfect knowledge about Willie's channel state information (WCSI). For the perfect WCSI case, the problem is formulated under the perfect covert constraint, and we develop a covert beamformer by applying semidefinite relaxation and the bisection method. Then, to reduce the computational complexity, we further propose a zero-forcing beamformer design with a single iteration processing. For the case of the imperfect WCSI, the robust beamformer is developed based on a relaxation and restriction approach by utilizing the property of Kullback-Leibler divergence. Furthermore, we derive the optimal decision threshold of Willie, and analyze the false alarm and the missed detection probabilities in this case. Finally, the performance of the proposed beamformer designs is evaluated through numerical experiments.
A major limitation of physical layer security is the requirement for prior knowledge of the potential eavesdroppers' (Eves) channels, which makes its practical implementation challenging. Integrated sensing and communication systems can be exploited to address this issue by enabling both communication and sensing functionalities, sensing the physical environment to estimate Eves' directions and amplitudes, and further reconstructing their channel state information (CSI) to achieve sensing-assisted wiretap channel awareness, thus realizing secure communication. We analyze a more practical scenario where not only is reconstructed Eves' CSI inaccurate, but also the CSI of the legitimate user equipments (UEs) estimated by the base station is imperfect, and Eves are equipped with multiple antennas. To resolve this, we propose a robust optimization problem that jointly maximizes the sensing accuracy and the secrecy rate by co-designing the beamforming and the artificial noise matrix. For the highly challenging non-convex infinite objective function, the S-Procedure is introduced, which is then solved by an efficient algorithm based on alternating optimization and successive convex approximation. Numerical results validate the effectiveness of the proposed algorithm and demonstrate that the robust beamforming scheme can mitigate the impact of channel uncertainty (both UEs' and Eves') on the system performance.
This paper investigates the covert communication in the scenario of counter detection. In traditional covert communication design where the uncertainty of the position of the Warden Willie typically reduces covert performance. To overcome this limitation, we leverage the sensing ability of the ISAC system in a new way to reduce the channel uncertainty between Alice and Willie, thereby enabling less conservative power allocation and significantly improving the achievable covert throughput. In the first stage, the dual functional sensing and communication (DFRC) base station Bob sends joint signals to estimate the azimuth of Willie and transmits information to Alice at the same time. In the second stage, Alice uses the obtained azimuth information of Willie to adjust transmit power while meeting the covert constraints. We build a mathematical model of azimuth angle estimation error and connect it with the Cramér-Rao Bound (CRB) to change it into distance error. This connects sensing accuracy with channel state information (CSI) uncertainty in a linear way, allowing Alice to adopt a higher transmit power while still satisfying the covert constraint, and thus improving the achievable covert throughput. To increase the covert throughput of the user, we use a layered solving strategy to decouple the original problem. First, we use S-procedure to change the constraint on possible distance error into a linear matrix inequality (LMI) constraint and then find the upper limit of transmit power on the user side. Second, we combine it with the uplink communication link rate constraint to find the closed form expression of the resource allocation strategy in vector space. Finally, we use one dimensional search to find the optimal time slot allocation strategy. Simulation results show that the proposed two-stage protocol effectively improves the achievable covert throughput by reducing position uncertainty through sensing.
In this article, we investigate joint information-theoretic secrecy and covert communication in a single-input-multioutput (SIMO) system where a transmitter (Alice) is communicating with two legitimate users (Bob and Carol). We consider that an untrusted user and a warden node are also present in the network attempting to attack the secure and covert communications to Bob and Carol, respectively. Specifically, Bob requires secure communications such that his messages from Alice are not decoded by the untrusted user, while Carol requires covert communications such that her messages from Alice are not detected by the warden. To do so, we consider that Alice transmits Carol's messages during selected time slots to hide them from the warden while also transmitting Bob's messages in each time slot contentiously. We formulate an optimization problem with the aim of maximizing the average rate subject to a covert communication requirement and a secure communications constraint. Since the proposed optimization problem is nonconvex, we utilize successive convex approximation to obtain a tractable solution. Moreover, we extend our proposed system model to multiple antenna Alice scenario and find beamforming vectors so that the average sum rate is maximized. Furthermore, we consider practical assumptions that Alice has imperfect knowledge of the warden's location and imperfect channel state information (CSI) of Bob and Carol. Our numerical examples highlight that the imperfect CSI at Carol has a more detrimental impact on the average rate compared to imperfect CSI at Bob.
We propose a joint covert beamforming design and jamming strategy to protect the communication process between Alice and Bob from being discovered by Willie with the help of another pair of neutral nodes. Specifically, with the help of irrelevant communication parties that commonly exist in practical communication scenarios, Jammer increases his transmission power by interfering with the neutral receiver, thus indirectly increasing the interference to Willie, which can be viewed as leveraging the force to make a big impact with a small effect. In our designed beamformer, we jointly optimize the beam power allocation factor, Alice’s transmission power, and Jammer’s transmission power when Alice transmits, to maximize the covert rate, which also maximizes Alice’s transmission power. In the perfect channel state information (CSI) scenario, the transformed optimization problem is solved via a one-dimensional search method and CVX solver. Due to the solution’s high complexity, we further propose a method to determine the optimal power allocation factor. For the imperfect Willie’s CSI scenario, three cases are investigated: Alice to Willie imperfect CSI, Transmitter to Willie imperfect CSI, and Jammer to Willie imperfect CSI. We utilize the S-procedure to tackle the optimization problem. Simulation results demonstrate the effectiveness of our proposed strategy.